Systems and methods for NextG edge computing capacity management

An edge computing device, comprising:

• a processor configured to:
• initialize a virtual Edge Enhanced Computing (vEEC) system by loading network configuration and identifying edge computing nodes (ECNs) and their capabilities;
• monitor network resources that include computing, cloud services, storage, networking, and security resources;
• determine resource requirements for one or more software applications or tasks within the vEEC system;
• dynamically scale the monitored network resources based on a result of the monitoring and the determined resource requirements;
• resolve network congestion by redistributing tasks among ECNs based on network traffic analysis of the dynamically scaled monitored network resources;
• implement failover to cloud resources for ECNs identified in the result monitoring as facing resource limitations;
• offload computational tasks, based on the monitoring and the determined resource requirements, from edge devices with limited resources to more powerful servers or ECNs;
• monitor network performance and resource utilization for adjustments;
• and
• refine resource allocation models and system configuration based on feedback and performance metrics.

A non-transitory processor readable media having stored thereon processor-executable instructions configured to cause a processor in an edge computing device perform operations for orchestrating network operations in a virtual Edge Enhanced Computing (vEEC) system, the operations comprising:

• initializing the vEEC system by loading network configuration and identifying edge computing nodes (ECNs) and their capabilities;
• monitoring network resources that include computing, cloud services, storage, networking, and security resources;
• determine resource requirements for one or more software applications or tasks within the vEEC system;
• dynamically scaling the monitored network resources based on a result of the monitoring and the determined resource requirements;
• resolving network congestion by redistributing tasks among ECNs based on network traffic analysis of the dynamically scaled monitored network resources;
• implementing failover to cloud resources for ECNs identified in the result monitoring as facing resource limitations;
• offloading computational tasks, based on the monitoring and the determined resource requirements, from edge devices with limited resources to more powerful servers or ECNs;
• monitoring network performance and resource utilization for adjustments;
• and
• refining resource allocation models and system configuration based on feedback and performance metrics.